Numerical analysis: Difference between revisions

Revision as of 09:57, 7 May 2004

Revision as of 22:08, 7 May 2004

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Much effort has been put in the development of methods for solving systems of linear equations. Standard methods are [[Gauss-Jordan elimination]] and [[LU-factorization]]. [[Iterative method]]s such as Conjugate Gradients are usually preferred for large systems.

The[[Root-finding problemalgorithm]]s ofare solvingused to solve nonlinear equations (they are called like this since a root of a function is usuallyan solvedargument byfor [[linearization]]which the function yields zero). If the function is [[derivative|differentiable]] and the derivative is known, then [[Newton's method]] is a popular choice.

A common case of equation-solving is the finding of ''roots'' of functions: that is to say, values of a real- or complex-valued function's input which give an output of zero. Algorithms to solve this class of problem are known as [[root-finding algorithm]]s.

===Optimization===